crt.means.r

For a cluster randomized trial with a continuous outcome, this function calculates the correlation
between a cluster's mean at baseline and at follow up based on various inputs.
For cross-sectional sampling of subjects,
that is, different subjects are measured at baseline and follow up, specify sac = 0.

Power and sample size calculations for a variety of study designs and
outcomes. Methods include t tests, ANOVA (including tests for interactions,
simple effects and contrasts), proportions, categorical data (chi-square tests
and proportional odds), linear, logistic and Poisson regression, alternative
and coprimary endpoints, power for confidence intervals, correlation
coefficient tests, cluster randomized trials, individually randomized group
treatment trials, multisite trials, treatment-by-covariate interaction effects
and nonparametric tests of location. Utilities are provided for
computing various effect sizes. Companion package to the book
"Power and Sample Size in R", Crespi (2025, ISBN:9781138591622).
Further resources available at <https://powerandsamplesize.org/>.

Catherine M. Crespi

powertools

Power and Sample Size Tools

Zichen Liu

Kristen M. McGreevy

crt.means.r function

<dl><dt>m</dt>
<dd>The number of measurements in each cluster at baseline and follow up.</dd>
<dt>icc</dt>
<dd>The intraclass correlation coefficient.</dd>
<dt>cac</dt>
<dd>The cluster autocorrelation.</dd>
<dt>sac</dt>
<dd>The subject autocorrelation.</dd></dl>

Arguments

Correlation between a cluster mean at baseline and follow up — crt.means.r

<dl>

<dt>m</dt>
<dd>The number of measurements in each cluster at baseline and follow up.</dd>


<dt>icc</dt>
<dd>The intraclass correlation coefficient.</dd>


<dt>cac</dt>
<dd>The cluster autocorrelation.</dd>


<dt>sac</dt>
<dd>The subject autocorrelation.</dd>

</dl>

crt.means.r: Correlation between a cluster mean at baseline and follow up

Description

Usage

Value

Arguments

Examples